Machine Learning-Based Tomato Leaf Disease Diagnosis Using Radiomics Features

Ahmed, Faisal (author): Department of Computer Science and Engineering, Premier University, Chattogram, Bangladesh

Naim Uddin Rahi, Mohammad (author): Department of Computer Science and Engineering, Premier University, Chattogram, Bangladesh

Uddin, Raihan (author): Department of Computer Science and Engineering, Premier University, Chattogram, Bangladesh

Sen, Anik (author): Department of Computer Science and Engineering, Premier University, Chattogram, Bangladesh

Shahadat Hossain, Mohammad (author): University of Chittagong, Chattogram, Bangladesh

(creator_code:org_t)

Springer Science and Business Media Deutschland GmbH, 2023
2023
English.
In: Proceedings of the Fourth International Conference on Trends in Computational and Cognitive Engineering - TCCE 2022. - : Springer Science and Business Media Deutschland GmbH. - 9789811994821 - 9789811994838 ; , s. 25-35

Related links:: https://urn.kb.se/re...; show more...; https://doi.org/10.1...; show less...

Abstract Subject headings

Tomato leaves can be infected with various infectious viruses and fungal diseases that drastically reduce tomato production and incur a great economic loss. Therefore, tomato leaf disease detection and identification are crucial for maintaining the global demand for tomatoes for a large population. This paper proposes a machine learning-based technique to identify diseases on tomato leaves and classify them into three diseases (Septoria, Yellow Curl Leaf, and Late Blight) and one healthy class. The proposed method extracts radiomics-based features from tomato leaf images and identifies the disease with a gradient boosting classifier. The dataset used in this study consists of 4000 tomato leaf disease images collected from the Plant Village dataset. The experimental results demonstrate the effectiveness and applicability of our proposed method for tomato leaf disease detection and classification.

NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
LANTBRUKSVETENSKAPER -- Lantbruksvetenskap, skogsbruk och fiske -- Trädgårdsvetenskap/hortikultur (hsv//swe)
AGRICULTURAL SCIENCES -- Agriculture, Forestry and Fisheries -- Horticulture (hsv//eng)

By the author/editor: Ahmed, Faisal; Naim Uddin Rahi, ...; Uddin, Raihan; Sen, Anik; Shahadat Hossain ...; Andersson, Karl

About the subject

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Computer Science ...

AGRICULTURAL SCIENCES: AGRICULTURAL SCI ...; and Agriculture Fore ...; and Horticulture

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